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About

Niyati Rawal is a researcher specializing in human-robot interaction (HRI), affective computing, and responsible AI design, with a particular focus on bridging the gap between human emotional expression and robotic communication. Her most influential work, the highly cited survey "Facial Emotion Expressions in Human–Robot Interaction" (2022, 109 citations), provides a comprehensive overview of both human facial expression recognition and robotic facial expression generation, establishing her as a key voice in this rapidly evolving field. Building on this foundation, her ExGenNet framework (21 citations) introduced a novel deep learning approach to automate robotic facial expression generation, moving beyond rigid, preprogrammed configurations toward more naturalistic and socially aware robot behavior. Rawal has also made significant contributions to the ethical dimensions of HRI, co-authoring work examining responsible design principles for anthropomorphic service robots, addressing critical concerns around human dignity, privacy, and transparency as robots increasingly enter everyday life. Her most recent work on intelligent multimodal agents that talk and express emotions signals a continued push toward more holistic, emotionally intelligent artificial systems. Across her research, Rawal consistently works at the intersection of technical innovation and human-centered design, making her scholarship valuable to both engineers and social scientists alike.